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Analyzing and Preventing Data Privacy Leakage in Connected Vehicle Services

Ford Motor Co., Ltd.-Yu Seung Kim, Pramita Mitra
University of Michigan-Huaxin Li, Di Ma, Brahim Medjahed
  • Technical Paper
  • 2019-01-0478
To be published on 2019-04-02 by SAE International in United States
The rapid development of connected and automated vehicle technologies together with cloud-based mobility services are revolutionizing the transportation industry. As a result, huge amounts of data are being generated, collected, and utilized, hence providing tremendous business opportunities. However, this big data poses serious challenges mainly in terms of data privacy. The risks of privacy leakage are amplified by the information sharing nature of emerging mobility services and the recent advances in data analytics. In this paper, we first provide an overview of the connected vehicle landscape and point out potential privacy threats. We demonstrate two of the risks, namely additional individual information inference and user de-anonymization, through concrete attack designs. Our experiments on real-world datasets show that the individual information inference and user de-anonymization attacks are feasible in corresponding scenarios. We also propose corresponding countermeasures to defend against such privacy attacks and consider maintaining data usability at the same time. We evaluate the feasibility of our defense strategies using real-world vehicular data.

Industry 4.0 and Automotive 4.0: challenges and opportunities for designing new vehicle components for Automated and/or Electric Vehicles

Politecnico di Milano-Gianpiero R M Mastinu, Francesco cadini, Massimiliano Gobbi
  • Technical Paper
  • 2019-01-0504
To be published on 2019-04-02 by SAE International in United States
The interrelationship between the respective paradigms of Industry 4.0 and Automotive 4.0 are addressed, with focus on the central role of automotive components. Industry 4.0 activities are focused on the pervasive digitalization of production processes, Automotive 4.0 is focused on the digitalization of the mobility process. In the middle of such two big and pervasive digitalization courses, a crucial role is played by automotive components. The sensorization of components may be useful both for the digitalization of the manufacturing process but also for the monitoring, during lifetime use, of both automotive components and the whole vehicle. Sensorization is expensive, but: it is useful for reducing production costs, it allows substantial mass reduction (lightweight construction, improving Electric Vehicle range), it may be useful or even necessary for Automated vehicles to allow a proper constant monitoring for safety purposes. Sensorization should avoid a heavy and vulnerable cable network within the vehicle. So a proper wireless communication technology is to be developed. The above concepts have a great impact on both active and passive safety. Referring to active…

48V Boost Recuperation Systems – Golden Gate into the Future

SEG Automotive North America LLC-JUERGEN SCHNEIDER
  • Technical Paper
  • 2019-01-0391
To be published on 2019-04-02 by SAE International in United States
Automotive technology will be shaped mainly by the markets North America, Europe and China which account for more than two thirds of the yearly global car production. All three markets have partly challenging fuel consumption, CO2 and emission regulations in place and under discussion, which are forcing the automotive industry to improve their power train technology. But not only governmental regulations are driving the change, increasing urbanization intensifies local environmental pollution from vehicles and strains the acceptance of today’s car centric mobility. Electrification is the highly touted magic solution, but is it fast and comprehensive enough to solve above mentioned problems? Is society – car owners, automotive industry and governments – willing to pay the high cost for electrified car technology and infrastructure within a short time frame of 10 to 15 years? Or will most likely so called bridge technologies like 48V boost recuperation systems be needed, which are less efficient on a single car, but effective on a broad scale and therefore in total more beneficial and affordable overall. In Europe 48V BRS…

On Collecting High Quality Labeled Data for Automatic Transportation Mode Detection

Ford Motor Company-Prashant Rao, David Melcher, Pramita Mitra, Sriram Rao
  • Technical Paper
  • 2019-01-0921
To be published on 2019-04-02 by SAE International in United States
With the recent advancements in sensing and processing capabilities of consumer mobile devices (e.g., smartphone, tablet, etc.), they are becoming attractive choices for pervasive computing applications. Always-on monitoring of human movement patterns is one of those applications that has gained a lot of importance in the field of mobility and transportation research. Automatic detection of the current transportation mode (e.g., walking, biking, riding a shuttle, etc.) of a consumer using data from their smartphone sensors enables delivering of a number of customized services for multi-modal journey planning. Most accurate models for automatic mode detection are trained with supervised learning algorithms. In order to achieve high accuracy, the training datasets need to be sufficiently large, diverse, and correctly labeled. Specifically, the training data requires each type of mode data to be collected for a minimum duration that is necessary and sufficient for building high accuracy models. Collecting such data in an efficient manner is challenging because of the variability in the test subjects’ multi-modal journey patterns, e.g., using mostly private vehicles for commute, not sufficiently using…

Evaluating Location Privacy in Autonomous Vehicular Communications and Applications

Oakland University-Abdelnasser Banihani, Huirong Fu
Saginaw Valley State University-Abdulrahman Zaiter, George P. Corser
  • Technical Paper
  • 2019-01-0487
To be published on 2019-04-02 by SAE International in United States
Vehicular ad hoc networks may one day prevent injuries and reduce transportation costs by enabling new safety and traffic management applications, but these networks raise privacy concerns because they could enable applications to perform unwanted surveillance. Researchers have proposed privacy protocols, measuring privacy performance based on metrics such as k-anonymity. Because of the frequency and precision of location of queries in vehicular applications, privacy measurement may be improved by considering additional factors. This paper defines continuous network location privacy; presents KDT-anonymity, which is a composite metric including average anonymity set size, i.e., K, average distance deviation, i.e., D, and anonymity duration, i.e., T; derives formulas to calculate theoretical values of K, D, and T; evaluates five privacy protocols under realistic vehicle mobility patterns using KDT-anonymity; and compares KDT-anonymity with prior metrics.

Use of Hardware in the Loop (HIL) Simulation for Developing Connected Autonomous Vehicle (CAV) Applications

Ohio State University-Mustafa Ridvan Cantas, Ozgenur Kavas, Santhosh Tamilarasan, Sukru Yaren Gelbal, Levent Guvenc
  • Technical Paper
  • 2019-01-1063
To be published on 2019-04-02 by SAE International in United States
Many smart cities and car manufacturers have been investing in Vehicle to Infrastructure (V2I) applications by integrating the Dedicated Short Range Communication (DSRC) technology to improve the fuel economy, safety, and ride comfort for the end users. For example, Columbus, OH, USA is placing DSRC Road Side Units (RSU) to the traffic lights which will publish traffic light Signal Phase and Timing (SPaT) information. With DSRC On Board Unit (OBU) equipped vehicles, people will start benefiting from this technology. In this paper, a Hardware in the Loop (HIL) simulator with DSRC RSU and OBU to accelerate the V2I application development for Connected and Autonomous Vehicles (CAV) is presented. The developed HIL simulator environment is employed to implement, develop and evaluate V2I connected vehicle applications in a fast, safe and cost-effective manner. The prepared simulator allows realistic, real-time evaluation of mobility and fuel economy benefits over simulated actual routes in a safe lab setting before actual deployment in an experimental vehicle. To show the capabilities of the designed HIL simulator, a well-known eco-approach and eco-departure algorithm…

New Paradigm in Robust Infrastructure Scalability for Autonomous Applications.

Wayne State Univ.-Kyle W. Brown
  • Technical Paper
  • 2019-01-0495
To be published on 2019-04-02 by SAE International in United States
Artificial Intelligence (A.I.) and Big Data are increasing become more applicable in the development of technology from machine design and mobility to bio-printing and drug discovery. The ability to quantify large amounts of data these systems generate will be paramount to establishing a robust infrastructure for interdisciplinary applications. This paper purposes a new paradigm for the environment, pre/post data processing, integration, and system security for robust systems in mobility. The systems integration is based on a novel FPGA embedded system design and computing (EDGE) platform utilizing image processing c-NN algorithms from High Energy Physics (HEP) experiments with associative memory to ROS- FPGA technology for hyper-scale infrastructure scalability in autonomous applications. The ability to process data on this scale is equivalent to collision particle detection that LHC produces at CERN. The future of robust scalability will depend upon how seamlessly a number of applications can be integrated into a high performance package with low consumption. The proposed architecture will entirely be dependent on a digital network with special attention paid to costs and power consumption needed…

Mobile Laser Trackers for aircraft manufacturing: Increasing accuracy and productivity of robotic applications for large parts

FFT Produktionssysteme GmbH & Co KG-Fabian Ehmke
Fraunhofer IFAM-Christoph Brillinger, Till Staude, Kevin Deutmarg, Maximilian Klemstein, Christian Boehlmann
  • Technical Paper
  • 2019-01-1368
To be published on 2019-03-19 by SAE International in United States
The demand for higher production rates of large parts in aircraft industry requests more flexible manufacturing solutions. High-accurate mobile robots show a promising alternative in comparison with high-invest special machines. With mobile robot-based solutions processes can be executed simultaneously which increases the productivity significantly. However, the freedom of mobility results in insufficient positioning accuracy of these machines. Hence, fast and accurate referencing processes are required to achieve cost-effectiveness and meet production tolerances. Laser Trackers show an increasing maximum permissible error with increasing distance of the measurement target. For vast machines and components the achievable reference accuracy can be insufficient, due to high measurement distances. Visibility of measurement targets, especially for mobile machines, has a further limiting impact on finding suitable measurement positions. Therefore, often multiple systems are required at one station. By repositioning the measurement system visibility and accuracy can be optimized. As a manual process, this would cause higher effort and auxiliary process time. With mobile Laser Trackers the area of operation can be expanded while at the same time increasing the return on…

Servitization and Physical Asset Management

Michael John Provost
  • Book
  • R-479
Published 2018-12-31 by SAE International in United States

Servitization and Physical Asset Management, third edition, was developed to provide a structured source of guidance and reference information on the business opportunities linked to servitization and the management of physical assets.

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SAE Advanced Manufacturing Podcast: Transforming Mobility Development with Additive Manufacturing

  • Podcast
  • 12402
Recorded 2018-12-04

Dr. John Hart, Associate Professor of Mechanical Engineering and Director of the Center for Additive and Digital Advanced Production Technologies (ADAPT) at MIT explores the advantages of adopting additive manufacturing into production environments and workflows.